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DBLP
Article . 2014
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Choice Architecture for Human-Computer Interaction

Authors: Anthony Jameson; Bettina Berendt; Silvia Gabrielli; Federica Cena; Cristina Gena; Fabiana Vernero; Katharina Reinecke;

Choice Architecture for Human-Computer Interaction

Abstract

People in human-computer interaction have learned a great deal about how to persuade and influence users of computing technology. They have much less well-founded knowledge about how to help users choose for themselves. It’s time to correct this imbalance. A first step is to organize the vast amount of relevant knowledge that has been built up in psychology and related fields in terms of two comprehensive but easy-to-remember models: The ASPECT model answers the question “How do people make choices?” by describing six choice patterns that choosers apply alternately or in combination, based on Attributes, Social influence, Policies, Experience, Consequences, and Trial and error. The ARCADE model answers the question “How can we help people make better choices?” by describing six general high-level strategies for supporting choice: Access information and experience, Represent the choice situation, Combine and compute, Advise about processing, Design the domain, and Evaluate on behalf of the chooser. These strategies can be implemented with straightforward interaction design, but for each one there are also specifically relevant technologies. Combining these two models, we can understand virtually all existing and possible approaches to choice support as the application of one or more of the ARCADE strategies to one or more of the ASPECT choice patterns. After introducing the idea of choice architecture for humancomputer interaction and the key ideas of the ASPECT and ARCADE models, we discuss each of the ASPECT patterns in detail and show how the high-level ARCADE strategies can be applied to it to yield specific tactics. We then apply the two models in the domains of online communities and privacy. Most of our examples concern choices about the use of computing technology, but the models are equally applicable to everyday choices made with the help of computing technology.

Countries
Italy, Belgium
Keywords

0806 Information Systems, 1503 Business and Management, 3509 Transportation, logistics and supply chains, 1505 Marketing, 004

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
56
Top 10%
Top 10%
Top 10%
Green
gold